Optimizing the frequency of question items for bird species in quiz-style online training
Citizen science plays an important role in monitoring for biodiversity conservation. More efficient online training is needed to help citizens improve their species-identification skills, but such training remains a challenging task. We previously developed an online birdsong-identification training...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Ecological Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954124004503 |
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| author | Yui Ogawa Keita Fukasawa Akira Yoshioka Nao Kumada Akio Takenaka Takashi Kamijo |
| author_facet | Yui Ogawa Keita Fukasawa Akira Yoshioka Nao Kumada Akio Takenaka Takashi Kamijo |
| author_sort | Yui Ogawa |
| collection | DOAJ |
| description | Citizen science plays an important role in monitoring for biodiversity conservation. More efficient online training is needed to help citizens improve their species-identification skills, but such training remains a challenging task. We previously developed an online birdsong-identification training tool called TORI-TORE. However, its adaptive algorithm, in which question items regarding the species with lower correct answer rates for each user were presented more frequently, was not as effective as the conventional baseline training, in which the frequency of question items was uniform among species. In the present study, we introduce new algorithms, namely, the frequency-adjustment algorithm, which prioritizes species that are expected to have a large training effect, and the interactive algorithm, which allows users to adjust the frequency of question items regarding species by themselves. We then evaluate the effectiveness of the algorithms in a randomized controlled trial, based on test scores and questionnaire responses. At the same time, we compare the new algorithms with the previous adaptive algorithm. The frequency-adjustment group showed the most improvement in scores, ahead of the interactive group, the frequency-adjustment + interactive group, and the baseline group. The frequency-adjustment algorithm also improved scores to a greater extent compared with the adaptive algorithm implemented in our previous experiment in 2021. However, participants in the frequency-adjustment group had difficulty perceiving changes in their own interest in learning birdsongs, and so a future version of TORI-TORE may need to allow for the selection of not only the frequency-adjustment algorithm but also the frequency-adjustment + interactive algorithm. |
| format | Article |
| id | doaj-art-e0a3a14fc4824219bde0723f431a5bc6 |
| institution | Kabale University |
| issn | 1574-9541 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Informatics |
| spelling | doaj-art-e0a3a14fc4824219bde0723f431a5bc62025-01-19T06:24:32ZengElsevierEcological Informatics1574-95412025-03-0185102908Optimizing the frequency of question items for bird species in quiz-style online trainingYui Ogawa0Keita Fukasawa1Akira Yoshioka2Nao Kumada3Akio Takenaka4Takashi Kamijo5Degree Programs in Life and Earth Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan; Biodiversity Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan; Corresponding author at: Degree Programs in Life and Earth Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, Japan.Biodiversity Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, JapanFukushima Regional Collaborative Research Center, National Institute for Environmental Studies, 10-2 Fukasaku, Miharu, Fukushima 963-7700, JapanBiodiversity Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan; Japan Bird Research Association, 1-4-28-302 Higashi, Kunitachi, Tokyo, JapanUnaffiliated, C/O National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8577, JapanInstitute of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8577, JapanCitizen science plays an important role in monitoring for biodiversity conservation. More efficient online training is needed to help citizens improve their species-identification skills, but such training remains a challenging task. We previously developed an online birdsong-identification training tool called TORI-TORE. However, its adaptive algorithm, in which question items regarding the species with lower correct answer rates for each user were presented more frequently, was not as effective as the conventional baseline training, in which the frequency of question items was uniform among species. In the present study, we introduce new algorithms, namely, the frequency-adjustment algorithm, which prioritizes species that are expected to have a large training effect, and the interactive algorithm, which allows users to adjust the frequency of question items regarding species by themselves. We then evaluate the effectiveness of the algorithms in a randomized controlled trial, based on test scores and questionnaire responses. At the same time, we compare the new algorithms with the previous adaptive algorithm. The frequency-adjustment group showed the most improvement in scores, ahead of the interactive group, the frequency-adjustment + interactive group, and the baseline group. The frequency-adjustment algorithm also improved scores to a greater extent compared with the adaptive algorithm implemented in our previous experiment in 2021. However, participants in the frequency-adjustment group had difficulty perceiving changes in their own interest in learning birdsongs, and so a future version of TORI-TORE may need to allow for the selection of not only the frequency-adjustment algorithm but also the frequency-adjustment + interactive algorithm.http://www.sciencedirect.com/science/article/pii/S1574954124004503Citizen scienceQuiz-style online trainingBirdsong identificationSerious gameLearning outcomes |
| spellingShingle | Yui Ogawa Keita Fukasawa Akira Yoshioka Nao Kumada Akio Takenaka Takashi Kamijo Optimizing the frequency of question items for bird species in quiz-style online training Ecological Informatics Citizen science Quiz-style online training Birdsong identification Serious game Learning outcomes |
| title | Optimizing the frequency of question items for bird species in quiz-style online training |
| title_full | Optimizing the frequency of question items for bird species in quiz-style online training |
| title_fullStr | Optimizing the frequency of question items for bird species in quiz-style online training |
| title_full_unstemmed | Optimizing the frequency of question items for bird species in quiz-style online training |
| title_short | Optimizing the frequency of question items for bird species in quiz-style online training |
| title_sort | optimizing the frequency of question items for bird species in quiz style online training |
| topic | Citizen science Quiz-style online training Birdsong identification Serious game Learning outcomes |
| url | http://www.sciencedirect.com/science/article/pii/S1574954124004503 |
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